9222075 Gonzalez-Lima Brain metabolic mapping techniques have the potential of providing information about functional interactions within entire neural systems. Large quantities of data can be obtained from mapping studies, but an analytic technique to make sense of the complex network interactions that take place in the brain has not been available. Structural modeling may provide such a technique by combining the anatomical connectivity with the covariation in the activity between brain regions. Functional strengths of anatomical connections between the structures that form a neural system could be quantified by assigning numerical values to the links. Changes in these values could be used as indices of how information is processed and modified within the brain in a given situation. The purpose of this proposal is to use existing metabolic data from auditory learning experiments to develop structural models of auditory and nonauditory systems. The proposed methods will also be evaluated using simulated data with known relationships.***
